nessai.livepoint

Functions related to creating live points and converting to other common data-types.

Module Contents

Functions

add_extra_parameters_to_live_points(parameters[, ...])	Add extra parameters to the live points dtype.
reset_extra_live_points_parameters()	Reset the extra live points parameters.
get_dtype(names[, array_dtype, non_sampling_parameters])	Get a list of tuples containing the dtypes for the structured array
empty_structured_array(n[, names, dtype, ...])	Get an empty structured array with the extra parameters initialised.
live_points_to_array(live_points[, names, copy])	Converts live points to unstructured arrays for training.
parameters_to_live_point(parameters, names[, ...])	Take a list or array of parameters for a single live point
numpy_array_to_live_points(array, names[, ...])	Convert a numpy array to a numpy structure array with the correct fields
dict_to_live_points(d[, non_sampling_parameters])	Convert a dictionary with parameters names as keys to live points.
live_points_to_dict(live_points[, names])	Convert a structured array of live points to a dictionary with
dataframe_to_live_points(df[, non_sampling_parameters])	Convert and pandas dataframe to live points.
unstructured_view(x[, names, dtype])	Get an unstructured view of a live points containing certain parameters.

nessai.livepoint.add_extra_parameters_to_live_points(parameters, default_values=None)

Add extra parameters to the live points dtype.

Extra parameters will be included in the live points dtype that is used for constructing/converting to/from live points.

Parameters:

parameters: list

List of parameters to add.

default_values: Optional[Union[List, Tuple]]

List of default values for each parameters. If not specified, default values will be set to based on :code: DEFAULT_FLOAT_VALUE in nessai.config.

nessai.livepoint.reset_extra_live_points_parameters()

Reset the extra live points parameters.

nessai.livepoint.get_dtype(names, array_dtype=None, non_sampling_parameters=True)

Get a list of tuples containing the dtypes for the structured array

Parameters:

nameslist of str

Names of parameters

array_dtypeOptional[str]

dtype to use

non_sampling_parametersbool

Indicates whether non-sampling parameters should be included.

Returns:

numpy.dtype

A instance of numpy.dtype.

nessai.livepoint.empty_structured_array(n, names=None, dtype=None, non_sampling_parameters=True)

Get an empty structured array with the extra parameters initialised.

Parameters:

nint

Length of the structured array

dtypeOptional[list]

Dtype to use. Must contain the non-sampling parameters.

namesOptional[list]

Names of fields (excluding non-sampling parameters) to construct the dtype. Must be specified if dtype is not specified.

non_sampling_parametersbool

Indicates whether non-sampling parameters should be included.

Returns:

np.ndarray

Structured array with the all parameters initialised to their default values.

nessai.livepoint.live_points_to_array(live_points, names=None, copy=False)

Converts live points to unstructured arrays for training.

Parameters:

live_pointsstructured_array

Structured array of live points

nameslist of str or None

If None all fields in the structured array are added to the dictionary else only those included in the list are added.

copybool

If true, returns a copy. If false, returns a view. See numpy documentation for numpy.lib.recfunctions.structured_to_unstructured for more details.

Returns:

np.ndarray

Unstructured numpy array

nessai.livepoint.parameters_to_live_point(parameters, names, non_sampling_parameters=True)

Take a list or array of parameters for a single live point and converts them to a live point.

Returns an empty array with the correct fields if len(parameters) is zero

Parameters:

parameterstuple

Float point values for each parameter

namestuple

Names for each parameter as strings

non_sampling_parametersbool

Indicates whether non-sampling parameters should be included.

Returns:

structured_array

Numpy structured array with fields given by names plus logP and logL

nessai.livepoint.numpy_array_to_live_points(array, names, non_sampling_parameters=True)

Convert a numpy array to a numpy structure array with the correct fields

Parameters:

arraynp.ndarray

Instance of np.ndarray to convert to a structured array

namestuple

Names for each parameter as strings

non_sampling_parametersbool

Indicates whether non-sampling parameters should be included.

Returns:

structured_array

Numpy structured array with fields given by names plus logP and logL

nessai.livepoint.dict_to_live_points(d, non_sampling_parameters=True)

Convert a dictionary with parameters names as keys to live points.

Assumes all entries have the same length. Also, determines number of points from the first entry by checking if the value has __len__ attribute, if not the dictionary is assumed to contain a single point.

Parameters:

ddict

Dictionary with parameters names as keys and values that correspond to one or more parameters

non_sampling_parametersbool

Indicates whether non-sampling parameters should be included.

Returns:

structured_array

Numpy structured array with fields given by names plus logP and logL

nessai.livepoint.live_points_to_dict(live_points, names=None)

Convert a structured array of live points to a dictionary with a key per field.

Parameters:

live_pointsstructured_array

Array of live points

nameslist of str or None

If None all fields in the structured array are added to the dictionary else only those included in the list are added.

Returns:

dict

Dictionary of live points

nessai.livepoint.dataframe_to_live_points(df, non_sampling_parameters=True)

Convert and pandas dataframe to live points.

Adds the non-sampling parameter initialised to their defaults.

Based on this answer on Stack Exchange: https://stackoverflow.com/a/51280608

Parameters:

dfpandas.DataFrame

Pandas DataFrame to convert to live points

non_sampling_parametersbool

Indicates whether non-sampling parameters should be included.

Returns:

structured_array

Numpy structured array with fields given by column names plus logP and logL.

nessai.livepoint.unstructured_view(x, names=None, dtype=None)

Get an unstructured view of a live points containing certain parameters.

This is quicker than converting to a unstructured array and does not create a copy of the array.

Parameters:

xnumpy.ndarray

Structured array.

namesOptional[Iterable]

Iterable of parameters to include in the view. Must be specified if dtype is None.

dtypeOptional[numpy.dtype]

Dtype for constructing the unstructured view.

Returns:

numpy.ndarray

View of x as an unstructured array that contains only the parameters in names/dtype. Shape is (x.size, # parameters).